Abstract
In this paper, we present a new approach of designing adaptive inverse controller for synchronous generator excitation system containing nonsmooth nonlinearities in actuator device. The proposed controller considers not only the dynamics of generator but also nonlinearities in actuator. To address such a challenge, support vector machines (SVM) is adopted to identify the plant and to construct the inverse controller. SVM networks, used to compensate nonlinearities in synchronous generator as well as in actuator, are adjusted online by an adaptive law via back propagation (BP) algorithm. To guarantee convergence and for fast learning, adaptive learning rate and convergence theorem are developed. Simulation results are given, showing satisfactory control performance and illustrate the potential of the proposed adaptive inverse controller as useful for practical purpose.
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Yuan, X., Wang, Y. & Wu, L. Adaptive Inverse Control of Excitation System with Actuator Uncertainty. Neural Process Lett 27, 125–136 (2008). https://doi.org/10.1007/s11063-007-9064-7
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DOI: https://doi.org/10.1007/s11063-007-9064-7